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- A data-mining based methodology for wind forecastingPublication . Ramos, Sérgio; Soares, João; Vale, Zita; Morais, H.In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.
- Using data mining techniques to support DR programs definition in smart gridsPublication . Vale, Zita; Morais, H.; Ramos, Sérgio; Soares, João; Faria, PedroIn recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.
- A Short Review on Data Mining Techniques for Electricity Customers CharacterizationPublication . Cembranel, Samuel S.; Lezama, Fernando; Soares, João; Filipe Ramos, Sérgio; Gomes, Antonio; Vale, ZitaAn important tool to manage electrical systems is the knowledge of customers' consumption patterns. Data Mining (DM) emerges as an important tool for extracting information about energy consumption in databases and identifying consumption patterns. This paper presents a short review on DM, with a focus on the characterization of electricity customers supported on knowledge discovery in database (KDD) process. The study includes several steps: first, few concepts of the KDD process are presented; following, a short review of clustering algorithms is presented including partitional, hierarchical, fuzzy, evolutionary methods, and Self-Organizing Maps; finally, the main concepts and methods for load classification, based on load shape indices are presented. The main objective of this work is to present a short review of DM techniques applied to identify typical load profiles in electrical systems and new customers' classification.
- Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsamplingPublication . Duarte, Jorge; Fred, Ana; Rodrigues, Fátima; Duarte, João; Ramos, Sérgio; Vale, ZitaWith the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.
- MV producers and consumers agents characterization with DSM techniquesPublication . Morais, H.; Ramos, Sérgio; Vale, Zita; Khodr, H. M.This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.
- Liberalization and customer behavior in the Portuguese residential retail electricity marketPublication . Fotouhi Ghazvini, Mohammad Ali; Ramos, Sérgio; Soares, João; Castro, Rui; Vale, ZitaThe final step that Portugal is taking to reach a fully liberalized electricity market is the deregulation of the retail market by phasing-out regulated electricity prices and reducing the administrative burdens in this area. These attempts are done to promote the entrance of companies into the retailing business and to actively engage the end-users in the market. This analysis shows that despite high consumer switching rates during the 2013–2015 period, the retail market in Portugal is still highly concentrated. The retail rates are also not following the changes in the wholesale market price.
- Goal Programming Approach for Energy Management of Smart BuildingPublication . Foroozandeh, Zahra; Ramos, Sérgio; Soares, João; Vale, ZitaIn this paper, a collective residential building is considered in which the following points are taken into consideration: (i) a flexibility value of Contract Power (CP) is considered for each consumer; (ii) it is assumed a single CP for the entire building; (iii) an energy resource manager entity is considered to manage the energy resources in the residential building, such as Electric Vehicles (EVs), Photovoltaic (PV) generation system, and the Battery Energy Storage System (BESS). Taking into consideration the previous assumptions, the major goal of this work is to minimize the electricity consumption costs of the residential building by using a Multi-Objective Mixed-Binary Linear Programming (MOMBLP) formulation. The objective function of the MOMBLP model minimizes the electricity cost consumption of each apartment. Then, a Goal Programming (GP) strategy is applied to find the most appropriate solutions for the proposed MOMBLP model. Finally, the performance of the suggested model is evaluated by comparing the obtained results from a Single-Objective Mixed-Binary Linear Programming (SOMBLP) approach in which the whole building consumption cost is minimized. The results show that using the GP strategy a reduction of 7.5% in the total annual energy consumption is verified in comparison with SOMBLP. Moreover, the GP approach leads to fair benefit among building consumers, by finding a solution with less distance from the desired level.
- A residential energy management system with offline population-based optimizationPublication . Soares, João; Lezama, Fernando; Ramos, Sérgio; Vale, Zita; Lopes, AndreExpectable improvements in battery technology and lower prices will certainly contribute to increase the interest in residential energy storage systems in the near future. The installment of photovoltaic panels and the use of energy storage systems will help to reduce power losses in distribution and transmission power grid and increase network availability, and consequently, to reduce the dependency on the use of fossil fuels. The paper presents a light implementation of residential energy management system that integrates photovoltaic generation, an energy storage system and an electric vehicle. The goal of the system is to reduce the costs of electric consumer energy bill. The effectiveness of the system is verified through its application in several scenarios for the Portuguese context. An offline population-based algorithm, namely differential evolution method is used to adjust the objective function for the online control of the energy devices in the residential house.
- Data mining applications in power systems - case-studies and future trendsPublication . Vale, Zita; Ramos, Carlos; Ramos, Sérgio; Pinto, TiagoPresently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.
- Charge/Discharge Scheduling of Electric Vehicles and Battery Energy Storage in Smart Building: a Mix Binary Linear Programming modelPublication . Foroozandeh, Zahra; Ramos, Sérgio Filipe Carvalho; Soares, João; Vale, Zita; Gomes, AntonioNowadays, the buildings have an important role in the high demand for electrical energy. Therefore, the energy management of the buildings may have significant influence on reducing the electricity consumption. Moreover, Electric Vehicles (EVs) have been considering as a power storage device in Smart Buildings (SBs) aiming to reduce the cost and consuming energy. Here, an energy management framework is proposed in which by considering the flexibility of the contracted power of each apartment, an optimal charging-discharging scheduled for EVs and Battery Energy Storage System (BESS) is defined over a long time period to minimize the electricity cost of the building. The proposed model is designed by a Mixed Binary Linear Programming formulation (MBLP) that the charging and discharging of EVs as well as BESS in each period is treated as binary decision variables. In order to validate the model, a case study involving three scenarios are considered. The obtained results indicate a 15% reduction in total electricity consumption cost and consumption energy by the grid over one year. Finally, the impact of capacity and charge/discharge rate of BESS on the power cost is analyzed and the optimal size of the BESS for assumed SB in the case study is also reported.