Strategic Bidding of Retailers in Wholesale Markets: Continuous Intraday Markets and Hybrid Forecast Methods

ABSTRACT: The deregulation process of the electricity sector has led to competition in wholesale and retail markets. In particular, retailers submit bids to wholesale markets to satisfy the energy needs associated with portfolios of end-use customers. This paper describes a strategic process for retailers bidding in a wholesale market composed of a day-ahead market, an intraday market, and a balancing market. It considers a market design that involves a hybrid model for the intraday market, based on daily auctions and a continuous procedure. The paper also presents a computational study to illustrate and test both the market design and the strategic bidding process of retailers. The results confirm the advantages of considering a continuous intraday market, show that bidding in short-term markets is more beneficial than bidding in medium-term markets, and indicate important aspects to consider when selecting customers to add to the portfolios of retailers.info:eu-repo/semantics/publishedVersio

Variable renewable energy and market design: new products and a real-world study

ABSTRACT: Most existing energy markets (EMs) were not designed to take into account an active participation of variable renewable energy (VRE). This situation results typically in imbalances and substantial costs in balancing markets. Such costs are reflected both in the energy and the VRE parts of the consumer tariffs. Both appropriate market products and new elements of market design may largely facilitate the large-scale integration of VRE in EMs. Accordingly, this article presents a new bilateral energy contract and introduces two new marketplaces that can contribute to reduce the imbalances resulting from VRE producers. It also presents a study conducted with the help of an agent-based tool, called MATREM. The results indicate a significant decrease in the imbalances and the associated costs.info:eu-repo/semantics/publishedVersio

Changing the day-ahead gate closure to wind power integration: a simulation-based study

ABSTRACT: Currently, in most European electricity markets, power bids are based on forecasts performed 12 to 36 hours ahead. Actual wind power forecast systems still lead to large errors, which may strongly impact electricity market outcomes. Accordingly, this article analyzes the impact of the wind power forecast uncertainty and the change of the day-ahead market gate closure on both the market-clearing prices and the outcomes of the balancing market. To this end, it presents a simulation-based study conducted with the help of an agent-based tool, called MATREM. The results support the following conclusion: a change in the gate closure to a time closer to real-time operation is beneficial to market participants and the energy system generally.info:eu-repo/semantics/publishedVersio

Efficient Communication in Agent-based Autonomous Logistic Processes

Transportation of goods plays a vital role for the success of a logistics network. The ability to transport goods quickly and cost effectively is one of the major requirements of the customers. Dynamics involved in the logistics process like change or cancellation of orders or uncertain information about the orders add to the complexity of the logistic network and can even reduce the efficiency of the entire logistics process. This brings about a need of integrating technology and making the system more autonomous to handle these dynamics and to reduce the complexity. Therefore, the distributed logistics routing protocol (DLRP) was developed at the University of Bremen. In this thesis, DLRP is extended with the concept of clustering of transport goods, two novel routing decision schemes and a negotiation process between the cluster of goods and the vehicle. DLRP provides the individual logistic entities the ability to perform routing tasks autonomously e.g., discovering the best route to the destination at the given time. Even though DLRP seems to solve the routing problem in real-time, the amount of message flooding involved in the route discovery process is enormous. This motivated the author to introduce a cluster-based routing approach using software agents. The DLRP along with the clustering algorithm is termed as the cluster-based DLRP. In the latter, the goods are first clustered into groups based on criteria such as the common destination. The routing is now handled by the cluster head rather than the individual transport goods which results in a reduced communication volume in the route discovery. The latter is proven by evaluating the performance of the cluster-based DLRP approach compared to the legacy DLRP. After the routing process is completed by the cluster heads, the next step is to improve the transport performance in the logistics network by identifying the best means to transport the clustered goods. For example, to have better utilization of the transport capacity, clusters can be transported together on a stretch of overlapping route. In order to make optimal transport decisions, the vehicle calculates the correlation metric of the routes selected by the various clusters. The correlation metric aids in identifying the clusters which can be transported together and thereby can result in better utilization of the transport resources. In turn, the transportation cost that has to be paid to the vehicle can be shared between the different clusters. The transportation cost for a stretch of route is calculated by the vehicle and offered to the cluster. The latter can decide based upon the transportation cost or the selected route whether to accept the transport offer from the vehicle or not. In this regard, different strategies are developed and investigated. Thereby a performance evaluation of the capacity utilization of the vehicle and the transportation cost incurred by the cluster is presented. Finally, the thesis introduces the concept of negotiation in the cluster based routing methods. The negotiation process enhances the transport decisions by giving the clusters and the vehicles the flexibility to negotiate the transportation cost. Thus, the focus of this part of the thesis is to analyse the negotiation strategies used by the logistics entities and their role in saving negotiation time while achieving a favorable transportation cost. In this regard, a performance evaluation of the different proposed strategies is presented, which in turn gives the logistics practitioners an overview of the best strategy to be deployed in various scenarios. Clustering of goods aid in the negotiation process as on the one hand, a group of transport goods have a stronger basis for negotiation to achieve a favorable transportation price from the vehicle. On the other hand it makes it easier for the vehicle to select the packages for transport and helps the vehicle to operate close to its capacity. In addition, clustering enables the negotiation process to be less complex and voluminous. From the analytical considerations and obtained results in the three parts of this thesis, it can be concluded that efficient transport decisions, though very complex in a logistics network, can be simplified to a certain extent utilizing the available information of the goods and vehicles in the network

Análise da Influência da Produção Eólica sobre os Preços do Mercado Ibérico de Eletricidade

A reestruturação do setor elétrico, as metas internacionais e os elevados mecanismos de apoio implementados, contribuíram para o crescimento exponencial da potência instalada das tecnologias renováveis. Como as tecnologias renováveis têm baixos custos marginais, a integração de maiores percentagens de produção renovável nos mercados de energia elétrica tem um impacto inevitável no seu funcionamento e nos preços da bolsa diária de energia. Como tal, nesta dissertação pretende-se quantificar o impacto da produção de energia eólica nos preços do mercado Ibérico de eletricidade. O efeito em questão denomina-se de “efeito da ordem de mérito” (EOM) e tem como principal consequência uma redução dos preços de mercado. Para calcular esta redução, durante o ano de 2017, recorreu-se a um simulador multi-agente, denominado de MATREM. Com o intuito de estabelecer o número de agentes intervenientes em cada simulação e para auxiliar na definição das propostas dos agentes foi desenvolvido o programa MACREOM. As simulações basearam-se em dados reais do mercado. Os resultados obtidos indicam que a comercialização de energia eólica diminuiu consideravelmente os preços de mercado, estimando-se uma redução média de 10.9 ¿/MWh em 2017. Considerando o caso específico de Portugal, esta redução correspondeu a um volume financeiro de 2313.8 milhões de euros. As tarifas feed-in tornaram-se no mecanismo de apoio às energias renováveis mais utilizado. Este mecanismo tem originado diversos debates, devido aos elevados custos a que os consumidores estão sujeitos. Porém, a maioria das análises realizadas não incluem as poupanças trazidas pelo EOM. Desta forma, considerando o volume financeiro, o valor de mercado da energia eólica e o montante total dos incentivos pagos aos produtores de energia eólica, estimou-se o custo líquido do mecanismo de apoio em Portugal. Para o período estudado, obteve-se um custo negativo, indicando uma poupança líquida de 1781.5 milhões de euros, um resultado experimental que suporta a adequabilidade e a continuidade da política energética seguida pelo país durante os últimos anos

A Framework for Argumentation-Based Agent Negotiation in Uncertain Settings

Automated negotiation technologies are being increasingly used in business applications, especially in the e-Commerce domain. Argumentation-Based Negotiation (ABN), among the existing approaches, has been distinguished as a powerful approach to automated negotiation due to its ability to provide more sophisticated information (arguments) that justifies and supports agents’ proposals in order to mutually influence their preference relations on the set of offers, and consequently on the negotiation outcome. During the recent years, argumentation-based negotiation has received a considerable attention in the area of agent communication. However, current proposals are mostly concerned with presenting protocols for showing how agents can interact with each other, and how arguments and offers can be generated, evaluated and exchanged under the assumption of certainty. Therefore, none of these proposals is directly targeting the agents’ uncertainty about the selection of their moves nor designing the appropriate negotiation strategies based on this uncertainty in order to help the negotiating agents better make their decisions in the negotiation settings where agents have limited or uncertain information, precluding them from making optimal individual decisions. In this thesis, we tackle the aforementioned problems by advocating an Argumentation-Based Agent Negotiation (ABAN) framework that is capable of handling the problem of agents’ uncertainty during the negotiation process. We begin by proposing an argumentation framework enriched with a new element called agent’s uncertainty as an important parameter in the agent theory to allow negotiating agents to decide which moves to play and reason about the selection of these moves under the assumption of uncertainty. Then, a method for agents’ uncertainty assessment is presented. In particular, we use Shannon entropy to assess agent’s uncertainty about their moves at each dialogue step as well as for the whole dialogue. Negotiation strategies and agent profiles issues are also explored and a methodology for designing novel negotiation strategies and agent profiles under the assumption of uncertainty is developed. Moreover, two important outcome properties namely, completeness and Nash equilibrium are discussed. Finally, the applicability of our framework is explored through several scenarios of the well-known Buyer/Seller case study. The obtained empirical results confirm the effectiveness of using our uncertainty-aware techniques and demonstrate the usefulness of using such techniques in argumentation-based negotiations

Concession Behaviour in Automated Negotiation

Abstract. Traditional negotiation, conducted face-to-face and via mail or telephone, is often difficult to manage, prone to misunderstanding, and time consuming. Automated negotiation promises a higher level of process efficiency, and more importantly, a faster emergence and a higher quality of agreements. The potential monetary impact has led to an increasing demand for systems composed of software agents representing individuals or organizations and capable of reaching efficient agreements. At present, work on automated negotiation has generated many useful ideas and concepts leading to important theories and systems. Yet, the design of software agents with negotiation competence largely lacks systematic, traceable, and reproducible approaches, and thus remains more an art than a science. Against this background, this paper presents a model for software agents that handles two-party and multi-issue negotiation. The model incorporates various concession strategies and negotiation tactics. Concession strategies are computationally tractable functions that define the tactics to be used both at the outset and throughout negotiation. Tactics, in turn, are functions that specify the short-term moves to be made at each point of negotiation

Concession behaviour in automated negotiation

Traditional negotiation, conducted face-to-face and via mail or telephone, is often difficult to manage, prone to misunderstanding, and time consuming. Automated negotiation promises a higher level of process efficiency, and more importantly, a faster emergence and a higher quality of agreements. The potential monetary impact has led to an increasing demand for systems composed of software agents representing individuals or organizations and capable of reaching efficient agreements. At present, work on automated negotiation has generated many useful ideas and concepts leading to important theories and systems. Yet, the design of software agents with negotiation competence largely lacks systematic, traceable, and reproducible approaches, and thus remains more an art than a science. Against this background, this paper presents a model for software agents that handles two-party and multi-issue negotiation. The model incorporates various concession strategies and negotiation tactics. Concession strategies are computationally tractable functions that define the tactics to be used both at the outset and throughout negotiation. Tactics, in turn, are functions that specify the short-term moves to be made at each point of negotiation