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- Congenital heart defects in isolated and syndromic contextPublication . Silva, Cátia; Varela, Catarina; Almeida, Cláudia; Gomes, Marcos; Brochado, Paulo; Nogueira, RoseteCongenital heart defects (CHD) is defined as a coarse structural abnormality of the heart or intrathoracic large vessels and which has functional significance. The objectives of this study were to determine the percentage of CHD in fetal autopsies and its frequency in isolated and syndromic context evaluate the most frequent types of CHD and determine the impact of histological study in the diagnosis of cardiac structural abnormalities.
- Real-Time Approach for Demand Response Tariffs Definition Using Decision TreesPublication . Silva, Cátia; Faria, Pedro; Vale, ZitaGiving the small resources more information about the transactions in the market will have a great influence on the balance and increase the uncertainty. Business models that are prepared to deal with small consumers and/or with small Distributed Generation units need to emerge to deal with this problem. The authors present a methodology able to minimize the operation costs for the Aggregator of these small resources but also find a fair remuneration according to their participation in the management of the local grid. The methodology could be explored by two approaches depending on time horizon: planning or operation. In the present paper, the two will be compared showing the viability of the path selected by the authors for the real-time approach - assign a remuneration group to a consumer considering the actual participation and the rules provided by a classification method.
- Study of Multi-Tariff Influence on the Distributed Generation RemunerationPublication . Silva, Cátia; Faria, Pedro; Vale, ZitaThe energy market, with the introduction of the smart grids concept, opens the door to small distributed energy resources. However, these resources introduce an added level of difficulty to market management, requiring an entity to aggregate and manage them optimally. This paper proposes an approach that integrates these small resources. The methodology is composed of optimal scheduling, aggregation and remuneration based on aggregation. The method chosen for aggregation is k-means. In relation to previous works, the innovation goes through the multi-period and the comparison that this can have in the formation of groups. Thus, three scenarios were created: Whole Week, Work Days and Weekend. Profiles were added for 548 units of DG. The justification for the formation of groups will be a fairer remuneration and according to the contribution of each resource to the management of the network.
- Rating the participation in Demand Response events with a contextual approach to improve accuracy of aggregated schedulePublication . Silva, Cátia; Faria, Pedro; Vale, Zita; Terras, José M.; Albuquerque, SuseteThe flexibility provided by the demand side will be crucial to take a step forward to increase the penetration of renewable energy resources in the system. The proposed methodology provides the aggregator with information about the most reliable consumers, attributing a trustworthy rate that characterizes their performance on Demand Response (DR) events. The innovation relies on applying rates and evaluating the context in which the event is triggered and the factors that influence such rates. The authors find that context is essential to understand which participants are available for the event and achieve the reduction target successfully. Also, the proposed methodology focuses on the performance and the proper motivation for continuous participation, reducing the uncertainty of the response in DR events by giving higher economic compensation to the active consumers with better results. Distributed generation is also optimally managed by the aggregator. Findings prove the feasibility of the proposed methodology supporting the Aggregator in communities and smart cities management.
- Aggregation of Consumers and Producers in a Community with different Clustering MethodsPublication . Silva, Cátia; Faria, Pedro; Vale, Zita; Starzacher, NikolausThe consumer concept is shaping up as the grid is improving to a smart way. Moving from an actor with little information about what was happening in the energy market, to player with an active and important role in its management. The term prosumer will revolutionize the way the electrical system operates. The possibility of the participation of distributed small-scale energy resources in the network infrastructure changes the current management model. The authors propose a model that optimally associates all concepts. Scheduling, aggregation and compensation are the main phases that compose this model. In this paper, the author focusses only on the second, being the main goal compare between being a consumer, a producer or a prosumer in this method. In this way, two partitional clustering methods were used, testing different k clusters.
- Assessment of Distributed Generation Units Remuneration Using Different Clustering Methods for AggregationPublication . Silva, Cátia; Faria, Pedro; Vale, ZitaThe stakeholders that belong to the energy market will have to adapt to the changes that the implementation of the concept of Smart Grid imposes. This concept requires new business models that include the demand response programs, the use of distributed generation and especially the remuneration that will be made for their contribution. The exposed methodology can be presented as a solution for virtual power players in this new challenge. Throughout this article, this methodology was tested regarding the remuneration of aggregate groups of distributed generation. It will also be analyzed the meaning of this tariff for both sides - aggregator and producers.
- Long-Term Smart Grid Planning Under Uncertainty Considering Reliability IndexesPublication . Canizes, Bruno; Soares, João; Fotouhi Ghazvini, Mohammad Ali; Silva, Cátia; Vale, Zita; Corchado, Juan M.The electricity sector is fast moving towards a new era of clean generation devices dispersed along the network. On one hand, this will largely contribute to achieve the multi-national environment goals agreed via political means. On the other hand, network operators face new complexities and challenges regarding network planning due to the large uncertainties associated with renewable generation and electric vehicles integration. In addition, due to new technologies such as combined heat and power (CHP), the district heat demand is considered in the long-term planning problem. The 13-bus medium voltage network is evaluated considering the possibility of CHP units but also without. Results demonstrate that CHP, together with heat-only boiler units, can supply the district heat demand and contribute to network reliability. They can also reduce the expected energy not supplied and the power losses cost, avoiding the need to invest in new power lines for the considered lifetime project.
- Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering MethodsPublication . Silva, Cátia; Faria, Pedro; Vale, ZitaNowadays, the data can be considered an asset when properly managed. An entity with the right tool to analyse the amount of data existent and withdraw crucial information will have the power to obliterate the competition. In the Energy sector, with Smart Grid introduction, small resources have more influence in the market through Demand Response and bidirectional communication. However, none of the actual business models is prepared to deal with the uncertainty related to these resources. The authors, in order to find a solution for this complex problem, proposed a methodology which the goal is to minimize operation costs and give fair compensation for resources who participate in the management of local markets. With this fair payment, it is expected continuous participation. Through clustering methods, remuneration groups are created. In the present paper, a study about the optimal number of clusters is performed. The information gives the Aggregator control in results of the following phases, understanding the impact in the remuneration of the resources.
- Clustering Support for an Aggregator in a Smart Grid ContextPublication . Silva, Cátia; Faria, Pedro; Vale, ZitaThe future of the industry foresees the automation and allocation of more intelligence to processes. A revolution in relation to the present. With this, new challenges and consequently more complexity is added to the management of the sectors. In the electric sector is introduced the theme of the Smart grids and so all the concepts aggregated with it. The possibility of the existence of demand response programs and the expansion of the distributed generation units for small players are key concepts and with enormous influence in the management of the markets belonging to this sector. Thus, a method is proposed that would help manage these resources through their aggregation, opening a new port for business models based on this idea. The benefit will be to take advantage of a more effective and efficient way the energy potential present in each group that is formed. Thus, in this paper will be explored the potential of clustering methods for the aggregation of resources.
- Classification Approaches to Foster the Use of Distributed Generation with Improved RemunerationPublication . Silva, Cátia; Faria, Pedro; Vale, ZitaThere are currently efforts to implement the concept of smart grids throughout the electric sector. This will bring radical changes to the entire management of the sector. The energy market does not run away from the rule. In this way, virtual power players will be required to update their business models to introduce all the concepts that the context of smart grids imposes. Thus, in this article is proposed a method that aggregates distributed generation and consumers who belong to demand response programs. Optimized scheduling, resource aggregation and classification of possible new resources, rescheduling, and remuneration are the phases of the methodology proposed and presented in this article. The focus will be on classification phase and the main objective is to create rules, through a previously trained model, to be able to classify the new resources and help with the challenges that virtual power players may face. Thus, five classification methods were tested and compared: neural networks, Bayesian naïve classification, decision trees, k-nearest neighbor method, and lastly support vector machine method.
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