Browsing by Author "Martins, A. Gomes"
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- Influence of the management perspective for choosing the best location for Distributed electric energy storage unitsPublication . Gonçalves, José; Pires Neves, Luís; Martins, A. GomesA methodology to assist a decision maker (DM) on the assessment of feasible solutions to implement a distributed electric energy storage system (DEESS) is presented. The chosen system is based on the nanophosphate lithium-ion battery technology due to its increasing use in electricity networks and to the advantages when compared to other commercially available technologies. The proposed methodology perfoms the choice of locations, using a definition of the best schedule of operation, while simultaneously optimizing four objective functions: the minimization of losses, voltage deviations and investment cost, and the maximization of the net gains of exploiting the differences among time varying energy prices. Results show that the best DEESS location depends on the energy service to be provided, namely of the goal of the DM that defines the management scheme of the DEESS, suggesting the need to incorporate this level of decision on the multiple objective formulation and making this methodology appropriate for different types of stakeholders.
- Network impact of residential energy management systems at city scalePublication . Miguel, Pedro; Neves, Luís; Martins, A. GomesThe impact on the electricity distribution system of residential energy management systems will result of changes in the electricity usage by consumers in response to stimuli like real-time changes in the electricity price. However, due to the dispersed and uncontrolled nature of the management of end-use appliances, estimating the energy and power output of an aggregation of such devices requires a specific approach. The proposed methodology makes use of information regarding total electricity consumption, queried data regarding the willingness of consumers to postpone the starting time of appliances operation and prototypes of hourly electricity price diagrams. The output of the methodology includes information on the released network capacity as well as on load rebound, both caused by the aggregated demand response. In particular, load rebound is a relevant phenomenon that presents new challenges to the management of the grid, and for which some preventive measures are suggested.
- Using clustering techniques to provide simulation scenarios for the smart gridPublication . Miguel, Pedro; Gonçalves, José; Pires Neves, Luís; Martins, A. GomestThe objective of this work is to obtain characteristic daily profiles of consumption, wind generationand electricity spot prices, needed to develop assessments of two different options commonly regardedunder the smart grid paradigm: residential demand response, and small scale distributed electric energystorage. The approach consists of applying clustering algorithms to historical data, namely using a hierar-chical method and a self-organizing neural network, in order to obtain clusters of diagrams representingcharacteristic daily diagrams of load, wind generation or electricity price. These diagrams are useful notonly to analyze different scenarios of combined existence, but also to understand their individual relativeimportance. This study enabled also the identification of a probable range of variation around an averageprofile, by defining boundary profiles with the maximum and minimum values of any cluster prototypes.