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- 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 Mixed Binary Linear Programming Model for Optimal Energy Management of Smart BuildingsPublication . Foroozandeh, Zahra; Ramos, Sérgio; Soares, João; Lezama, Fernando; Vale, Zita; Gomes, António; Joench, Rodrigo L.Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.
- 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.
- Data mining techniques for electricity customer characterizationPublication . Ramos, Sérgio Filipe Carvalho; Soares, João; Cembranel, Samuel S.; Tavares, Inês; Foroozandeh, Z.; Vale, Zita; Fernandes, RubipiaraThe liberalization of electricity markets has been resulted in the emergence of new players, increasing the competitiveness in the markets, standing those can provide better services for better prices. The knowledge of energy consumers’ profile has been an important tool to help players to make decisions in the electrical sectors. In this paper, a characterization model of typical load curves for Low Voltage (LV) customers is proposed and evaluated. The identification of consumption patterns is based on clustering analysis. The clustering methodology is based on seven algorithms, partitional and hierarchical. Also, five clustering validity indices are used to identify the best data partition. With the knowledge obtained in clustering analysis, a classification model is used to classify new customers according to their consumption data. The classification model is used to select the correct class for each customer. To make the model simple, each load curve is represented by three indices which represent load curves shape. The methodology used in this work demonstrates to be an effective tool and can be used in most diverse sectors, highlighting the use of knowledge in the optimization of the energy contracting for low voltage customers. The energy consumption data can be constantly updated to improve the model precision, finding estimates that can better represent consumers and their consumption habits.
- 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.
- 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.
- Single contract power optimization: A novel business model for smart buildings using intelligent energy managementPublication . Foroozandeh, Zahra; Ramos, Sérgio; Soares, João; Vale, Zita; Dias, MaurícioTypically, residential buildings neither allow flexibility in the individual contract power capacity nor considers buildings as unique electricity consumers. In this work, a smart building is designed that each electricity customer has flexible contract power and the whole collective residential building has a single contract power. A management entity is considered to manage all energy resources of the building such as the photovoltaic generation, electric vehicles, and battery energy storage system, taking into consideration the consumption from apartments and common services, to minimize the electricity bill. Hence, the best/optimal contract power capacity will contribute to minimizing electricity costs. Therefore, finding the optimal decision of the contract power value has received a significant role from the energy management in smart buildings. In this paper, a mixed binary optimization problem is formulated in which not only the optimal value of contract power is yield but the optimal schedule of the electric vehicle/battery storage charge and discharge are found, taking into consideration the photovoltaic generation and load consumption profiles. The proposed model is implemented for three scenarios, and the obtained results show that the model efficiency has a high performance with a significant electricity cost reduction, around 47%. The results pointed that using an optimal value of single contract power and intelligent management system, the building electricity costs decrease remarkably.
- Toward Retail Competition in the Portuguese Electricity MarketPublication . Ghazvini, Mohammad Ali Fotouhi; Ramos, Sérgio Filipe Carvalho; Soares, João; Vale, Zita; Castro, RuiPortugal has opened its’ retail electricity market for new entrants, while removing the burdens for competition among the supplier and customers’ switching between the electricity suppliers. The ultimate objective of this liberalization practice is to sharpen competition in the retail segment of the electricity market. In this paper, we assess the success of the liberalization process in the retail sector of the Portuguese electricity market by studying the customers’ behavior, changes in the retail rates and the market concentration. Finally, we provide some explanations for the high switching rates of the customers despite the increase in the retail rates. We also explain why the retail rates are not following the changes of the wholesale prices and the reason for the high market concentration in the retail segment.
- 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.
- 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.