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- MASCEM improvement for agent based coalitionsPublication . Praça, Isabel; Andrade, André; Morais, H.; Ramos, Carlos; Vale, ZitaThis paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.
- LEMMAS: a secured and trusted Local Energy Market simulation systemPublication . Andrade, Rui; Vitorino, João; Wannous, Sinan; Maia, Eva; Praça, IsabelThe ever changing nature of the energy grid and the addition of novel systems such as the Local Energy Market (LEM) drastically increase its complexity, thus making the management harder and with increased importance at local level. Providing innovative and advanced management solutions is fundamental for the success of this new distributed energy grid paradigm. In this paper we extend Multi-Agent System (MAS) based simulation tool for LEMs called LEMMAS. A cyberattack detection model is developed and integrated in LEMMAS with the objective of preventing cyber-attacks from affecting the negotiations. This model is compared with the previous version which only analysed the trustworthiness of participants. The results show that the cyber-attack detection model drastically increases the security capabilities of LEMMAS.
- Automated combination of bilateral energy contracts negotiation tacticsPublication . Pinto, Angelo; Pinto, Tiago; Silva, Francisco; Praça, Isabel; Vale, Zita; Corchado, Juan ManuelThis paper addresses the theme automated bilateral negotiation of energy contracts. In this work, the automatic combination between different negotiation tactics is proposed. This combination is done dynamically throughout the negotiation process, as result from the online assessment that is performed after each proposal and counter-proposal. The proposed method is integrated in a decision support system for bilateral negotiations, called Decision Support for Energy Contracts Negotiations (DECON), which in turn is integrated with the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM). This integration enables testing and validating the proposed methodology in a realistic market negotiation environment. A case study is presented, demonstrating the advantages of the proposed approach.
- Clustering-based negotiation profiles definition for local energy transactionsPublication . Pinto, Angelo; Pinto, Tiago; Praça, Isabel; Vale, Zita; Faria, PedroElectricity markets are complex and dynamic environments, mostly due to the large scale integration of renewable energy sources in the system. Negotiation in these markets is a significant challenge, especially when considering negotiations at the local level (e.g., between buildings and distributed energy resources). It is essential for a negotiator to be able to identify the negotiation profile of the players with whom he is negotiating. If a negotiator knows these profiles, it is possible to adapt the negotiation strategy and get better results in a negotiation. In order to identify and define such negotiation profiles, a clustering process is proposed in this paper. The clustering process is performed using the kml-k-means algorithm, in which several negotiation approaches are evaluated in order to identify and define players' negotiation profiles. A case study is presented, using as input data, information from proposals made during a set of negotiations. Results show that the proposed approach is able to identify players' negotiation profiles used in bilateral negotiations in electricity markets.
- Electricity Markets Simulation: MASCEM Contributions to the Challenging RealityPublication . Vale, Zita; Morais, H.; Pinto, Tiago; Praça, Isabel; Ramos, CarlosElectricity Markets are not only a new reality but an evolving one as the involved players and rules change at a relatively high rate. Multi-agent simulation combined with Artificial Intelligence techniques may result in sophisticated tools very helpful under this context. Some simulation tools have already been developed, some of them very interesting. However, at the present state it is important to go a step forward in Electricity Markets simulators as this is crucial for facing changes in Power Systems. This paper explains the context and needs of electricity market simulation, describing the most important characteristics of available simulators. We present our work concerning MASCEM simulator, presenting its features as well as the improvements being made to accomplish the change and challenging reality of Electricity Markets.
- Multi-agent Simulation of Bilateral Contracting in Competitive Electricity MarketsPublication . Lopes, Fernando; Algarvio, Hugo; Sousa, Jorge A. M.; Coelho, Helder; Pinto, Tiago; Santos, Gabriel; Vale, Zita; Praça, IsabelTraditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.
- Virtual power producers market strategiesPublication . Morais, H.; Cardoso, Marilio; Khodr, H. M.; Praça, Isabel; Vale, ZitaThis paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.
- Smart Grids Data Management: A Case for CassandraPublication . Pinheiro, Gil; Vinagre, Eugénia; Praça, Isabel; Vale, Zita; Ramos, CarlosThe objective of this paper is to present a SMACK based platform for microgrids data storage and management. The platform is being used in a real microgrid, with an infrastructure that monitors and controls 3 buildings within the GECAD - ISEP/IPP campus, while, at the same time, receives and manages data sources coming from different types of buildings from associated partners, to whom intelligent services are being provided. Microgrid data comes in different formats, different rates and with an increasing volume, as the microgrid itself covers more customers and areas. Based on the atual available computational resources, a Big Data platform based on the SMACK stack was implemented and is presented. The Cassandra component of the stack has evolved. AC version 2 is still supported until the version 4 release, and is often still used in production environments. However, a new stable version, version 3, introduces major optimizations in the storage that bring disk space savings. The main focus of this work is on the Data Storage and the formalization of the data mapping in Cassandra version 3, which is contextualized by means of a short example with data coming from the monitoring infrastructure of the microgrid.
- Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement LearningPublication . Silva, Francisco; Pinto, Tiago; Praça, Isabel; Vale, ZitaThis paper proposes an adaptation of the Q-Learning reinforcement learning algorithm, for the identification of the most probable scenario that a player may face, under different contexts, when negotiating bilateral contracts. For that purpose, the proposed methodology is integrated in a Decision Support System that is capable to generate several different scenarios for each negotiation context. With this complement, the tool can also identify the most probable scenario for the identified negotiation context. A realistic case study is conducted, based on real contracts data, which confirms the learning capabilities of the proposed methodology. It is possible to identify the most probable scenario for each context over the learned period. Nonetheless, the identified scenario might not always be the real negotiation scenario, given the variable nature of such negotiations. However, this work greatly reduces the frequency of such unexpected scenarios, contributing to a greater success of the supported player over time.
- A multi-agent based approach for intelligent smart grid managementPublication . Oliveira, Pedro; Vale, Zita; Morais, H.; Pinto, Tiago; Praça, IsabelThe spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.