Loading...
13 results
Search Results
Now showing 1 - 10 of 13
- Decision Support System for the Negotiation of Bilateral Contracts in Electricity MarketsPublication . Silva, Francisco; Teixeira, Brígida; Pinto, Tiago; Praça, Isabel; Marreiros, Goreti; Vale, ZitaThe use of Decision Support Systems (DSS) in the eld of Electricity Markets (EM) is essential to provide strategic support to its players. EM are constantly changing, dynamic environments, with many entities which give them a particularly complex nature. There are several simulators for this purpose, including Bilateral Contracting. However, a gap is noticeable in the pre-negotiation phase of energy transactions, particularly in gathering information on opposing negotiators. This paper presents an overview of existing tools for decision support to the Bilateral Contracting in EM, and proposes a new tool that addresses the identied gap, using concepts related to automated negotiation, game theory and data mining.
- D7.3 Proceedings of the Second DREAM-GO Workshop: Real-Time Demand Response and Intelligent Direct Load ControlPublication . Vale, Zita; Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Spínola, João; Canizes, Bruno; Pinto, Tiago; Soares, João; Chamoso, Pablo; Santos, Daniel; Garcia, Oscar; Catalina, Jorge; Guevarra, Fabio; Navarro-Cáceres, María; Gazafroudi, Amin Shokri; Prieto-Castrillo, Francisco; Corchado, Juan Manuel; Santos, Gabriel; Teixeira, Brígida; Praça, Isabel; Sousa, Filipe; Zawislak, Krzysztof; Iglesia, Daniel Hernández de la; Barriuso, Alberto Lopez; Lozano, Alvaro; Herrero, Jorge Revuelta; Landeck, Jorge; Paz, Juan F. de; Corchado, Juan M.; Garcia, Ruben Martin; González, Gabriel Villarrubia; Bajo, Javier; Matos, Luisa; Klein, L. Pires; Carreira, R.; Torres, I.; Landeck, JorgeProceedings of the Second DREAM-GO Workshop Real-Time Demand Response and Intelligent Direct Load Control
- Framework to Enable Heterogeneous Systems InteroperabilityPublication . Teixeira, Brígida; Pinto, Tiago; Santos, Gabriel; Praça, Isabel; Vale, ZitaThe electricity markets have been suffering profound changes over the years. Nowadays, the European Union comes to reformulate its politics related with renewable energy sources, in order to encourage microgeneration, having demand response as one of the biggest challenges. Various simulators have been developed that intend to give decision support to the various entities. However, they present the limitation of being designed to answer specific problems. This paper proposes the framework Tools Control Center (TOOCC) as the mechanism to integrate various independent and heterogeneous simulators, so they operate as a unique simulation tool and become capable of answering to more complex problems.
- Energy consumption forecasting based on Hybrid Neural Fuzzy Inference SystemPublication . Jozi, Aria; Pinto, Tiago; Praça, Isabel; Silva, Francisco; Teixeira, Brígida; Vale, ZitaForecasting the electricity consumption is one of the most challenging tasks for energy domain stakeholders. Having reliable electricity consumption forecasts can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study regarding the forecast of electricity consumption using a methodology based on Hybrid neural Fuzzy Inference System (HyFIS). The proposed approach considers two distinct strategies, namely one strategy using only the electricity consumption as the input of the method, and the second strategy uses a combination of the electricity consumption and the environmental temperature as the input. A case study considering the forecasting of the consumption of an office building using the proposed methodologies is also presented. Results show that the second strategy is able to achieve better results, hence concluding that HyFIS is an appropriate approach to incorporate different sources of information. In this way, the environmental temperature can help the HyFIS method to achieve a more reliable forecast of the electricity consumption.
- TOOCC: Enabling heterogeneous systems interoperability in the study of energy systemsPublication . Teixeira, Brígida; Silva, Francisco; Pinto, Tiago; Santos, Gabriel; Praça, Isabel; Vale, ZitaThe environmental impact and the scarcity of limited fossil fuels led to the need of investment in energy based on renewable sources. This has driven Europe to implement several policies that changed the energy market's paradigm, namely the incentive to microgeneration. The penetration of energy sources from intermittent nature has increased the unpredictability of the system, which makes simulation and analysis tools essential in order to provide decision support to entities in this sector. This paper presents the Tools Control Center (TOOCC) as a solution to increase the interoperability between heterogeneous agent-based systems, in the energy field. The proposed approach acts as a facilitator in the interaction between different systems through the usage of ontologies, allowing them to communicate in the same language. To understand the real applicability of this tool, a case study is presented concerning the interaction between several systems, with the purpose of enabling the energy resource scheduling of a microgrid, and the reaction of a house managed by a house management system.
- Application Ontology for Multi-Agent and Web-Services’ Co-Simulation in Power and Energy SystemsPublication . Teixeira, Brígida; Santos, Gabriel; Pinto, Tiago; Vale, Zita; Corchado, Juan M.Power and energy systems are very complex, and several tools are available to assist operators in their planning and operation. However, these tools do not allow a sensitive analysis of the impact of the interaction between the different sub-domains and, consequently, in obtaining more realistic and reliable results. One of the key challenges in this area is the development of decision support tools to address the problem as a whole. Tools Control Center - TOOCC - proposed and developed by the authors, enables the co-simulation of heterogeneous systems to study the electricity markets, the operation of the smart grids, and the energy management of the final consumer, among others. To this end, it uses an application ontology that supports the definition of scenarios and results comparison, while easing the interoperability among the several systems. This paper presents the application ontology developed. The paper addresses the methodology used for its development, its purpose and requirements, and its concepts, relations, facets and instances. The ontology application is illustrated through a case study, where different requirements are tested and demonstrated. It is concluded that the proposed application ontology accomplishes its goals, as it is suitable to represent the required knowledge to support the interoperability among the different considered systems.
- Multi-Agent Decision Support Tool to Enable Interoperability among Heterogeneous Energy SystemsPublication . Teixeira, Brígida; Pinto, Tiago; Silva, Francisco; Santos, Gabriel; Praça, Isabel; Vale, ZitaWorldwide electricity markets are undergoing a major restructuring process. One of the main reasons for the ongoing changes is to enable the adaptation of current market models to the new paradigm that arises from the large-scale integration of distributed generation sources. In order to deal with the unpredictability caused by the intermittent nature of the distributed generation and the large number of variables that contribute to the energy sector balance, it is extremely important to use simulation systems that are capable of dealing with the required complexity. This paper presents the Tools Control Center (TOOCC), a framework that allows the interoperability between heterogeneous energy and power simulation systems through the use of ontologies, allowing the simulation of scenarios with a high degree of complexity, through the cooperation of the individual capacities of each system. A case study based on real data is presented in order to demonstrate the interoperability capabilities of TOOCC. The simulation considers the energy management of a microgrid of a real university campus, from the perspective of the network manager and also of its consumers/producers, in a projection for a typical day of the winter of 2050.
- Applying real-time pricing for wind curtailment scenario using D2RD module of TOOCCPublication . Teixeira, Brígida; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaMulti-agent systems are widely used tools to simulate and study the energy sector because of their distributed architecture. There are several simulator tools available in literature, however, much of these prove to be very domain specific. The emergence of the Tools Control Center tool allows these simulators to cooperate in order to solve more comprehensive problems and more complex scenarios. This paper presents a module of this tool known as Demand Response Registration Digital, which allows the study of the model and programs of Demand Response. To understand the operation of this module, an example is given considering a wind curtailment scenario.
- Demonstration of Tools Control Center for Multi-agent Energy Systems SimulationPublication . Teixeira, Brígida; Silva, Francisco; Pinto, Tiago; Santos, Gabriel; Praça, Isabel; Vale, ZitaThe use of energy from renewable sources is one of the major concerns of today’s society. In recent years, the European Union has been changing legislation and implementing policies aimed at promoting its investment and encouraging its use in order to reduce the emission of greenhouse gases [1].
- Energy consumption forecasting using genetic fuzzy rule-based systems based on MOGUL learning methodologyPublication . Jozi, Aria; Pinto, Tiago; Praça, Isabel; Silva, Francisco; Teixeira, Brígida; Vale, ZitaOne of the most challenging tasks for energy domain stakeholders is to have a better preview of the electricity consumption. Having a more trustable expectation of electricity consumption can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study using a Methodology to Obtain Genetic fuzzy rule-based systems Under the iterative rule Learning approach (MOGUL) methodology in order to have a better profile of the electricity consumption of the following hours. The proposed approach uses the electricity consumption of the past hours to forecast the consumption value for the following hours. Results from this study are compared to those of previous approaches, namely two fuzzy based systems: and several different approaches based on artificial neural networks. The comparison of the achieved results with those achieved by the previous approaches shows that this approach can calculate a more reliable value for the electricity consumption in the following hours, as it is able to achieve lower forecasting errors, and a less standard deviation of the forecasting error results